Rena Lara, MS
How exposed is Rena Lara to wildfire?
Out of every US place USFS scores, Rena Lara lands at the 48th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 149 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Rena Lara's burn probability — fire likelihood with no building count factored in — sits at the 49th percentile nationally.
Rena Lara's building exposure, zone by zone
USFS classifies 73.2% of Rena Lara's buildings as Direct exposure, higher than its 26.9% Indirect share and far above its 0% Minimal share — a profile where 109 structures sit close enough to vegetation that lot clearing matters most.
How Rena Lara compares
Inside Mississippi, Rena Lara sits at just the 17th percentile even though it scores 48th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Rena Lara ranks 16,544 for wildfire risk (1 is highest) and 26,915 by building count (1 is largest). Within Mississippi alone, it ranks 347 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
What this risk score means for insurance
Rena Lara's elevated wildfire rating (48th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Rena Lara
Rena Lara's 73.2% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Rena Lara's figures come from
The methodology guide shows exactly how USFS turned 149 counted buildings into the percentiles shown above for Rena Lara. The exposure-zones guide covers what Rena Lara's dominant direct exposure actually means, with real examples from across the dataset.